Direction of arrival estimation in the presence of correlated signals with non-ideal uniform circular arrays

The Davies transformation is a method to transform
the steering vector of a uniform circular array (UCA) to a
vector with Vandermonde form. As this form is similar to
that of the steering vector of a uniform linear array
(ULA), we can apply to UCAs the many tools that have
been developed for ULAs. However, the Davies
transformation can be highly sensitive to perturbations of
the underlying ideal array model. In this paper, we present
two different methods for deriving a more robust
transformation. The main underlying idea is to trade off
robustness against accuracy of the Vandermonde form. In
particular, we consider its application to direction-of-
arrival estimation in the presence of correlated signals
using root Weighted Subspace Fitting (root-WSF). The
effectiveness of these methods are illustrated through
numerical examples.